Journal articles on the topic 'Ground based interferometric radar, ground based synthetic aperture radar, GB-SAR'

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1

Michelini, Alberto, Francesco Coppi, Alberto Bicci, and Giovanni Alli. "SPARX, a MIMO Array for Ground-Based Radar Interferometry." Sensors 19, no. 2 (January 10, 2019): 252. http://dx.doi.org/10.3390/s19020252.

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Ground-Based SAR Interferometry (GB-InSAR) is nowadays a proven technique widely used for slope monitoring in open pit mines and landslide control. Traditional GB-InSAR techniques involve transmitting and receiving antennas moving on a scanner to achieve the desired synthetic aperture. Mechanical movement limits the acquisition speed of the SAR image. There is a need for faster acquisition time as it plays an important role in correcting rapidly varying atmospheric effects. Also, a fast imaging radar can extend the applications to the measurement of vibrations of large structures. Furthermore, the mechanical assembly put constraints on the transportability and weight of the system. To overcome these limitations an electronically switched array would be preferable, which however faces enormous technological and cost difficulties associated to the large number of array elements needed. Imaging Multiple-Input Multiple Output (MIMO) radars can be used as a significant alternative to usual mechanical SAR and full array systems. This paper describes the ground-based X-band MIMO radar SPARX recently developed by IDS GeoRadar in order to overcome the limits of IDS GeoRadar’s well-established ground based interferometric SAR systems. The SPARX array consists of 16 transmit and 16 receive antennas, organized in independent sub-modules and geometrically arranged in order to synthesize an equally spaced virtual array of 256 elements.
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Hu, Jiyuan, Jiming Guo, Yi Xu, Lv Zhou, Shuai Zhang, and Kunfei Fan. "Differential Ground-Based Radar Interferometry for Slope and Civil Structures Monitoring: Two Case Studies of Landslide and Bridge." Remote Sensing 11, no. 24 (December 4, 2019): 2887. http://dx.doi.org/10.3390/rs11242887.

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Ground-based radar interferometry, which can be specifically classified as ground-based synthetic aperture radar (GB-SAR) and ground-based real aperture radar (GB-RAR), was applied to monitor the Liusha Peninsula landslide and Baishazhou Yangtze River Bridge. The GB-SAR technique enabled us to obtain the daily displacement evolution of the landslide, with a maximum cumulative displacement of 20 mm in the 13-day observation period. The virtual reality-based panoramic technology (VRP) was introduced to illustrate the displacement evolutions intuitively and facilitate the following web-based panoramic image browsing. We applied GB-RAR to extract the operational modes of the large bridge and compared them with the global positioning system (GPS) measurement. Through full-scale test and time-frequency result analysis from two totally different monitoring methods, this paper emphasized the 3-D display potentiality by combining the GB-SAR results with VRP, and focused on the detection of multi-order resonance frequencies, as well as the configure improvement of ground-based radars in bridge health monitoring.
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3

Miccinesi, Lapo, Tommaso Consumi, Alessandra Beni, and Massimiliano Pieraccini. "W-band MIMO GB-SAR for Bridge Testing/Monitoring." Electronics 10, no. 18 (September 14, 2021): 2261. http://dx.doi.org/10.3390/electronics10182261.

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Interferometric radars are widely used for static and dynamic monitoring of large structures such as bridges, culverts, wind turbine towers, chimneys, masonry towers, stay cables, buildings, and monuments. Most of these radars operate in Ku-band (17 GHz). Nevertheless, a higher operative frequency could allow the design of smaller, lighter, and faster equipment. In this paper, a fast MIMO-GBSAR (Multiple-Input Multiple-Output Ground-Based Synthetic Aperture Radar) operating in W-band (77 GHz) has been proposed. The radar can complete a scan in less than 8 s. Furthermore, as its overall dimension is smaller than 230 mm, it can be easily fixed to the head of a camera tripod, which makes its deployment in the field very easy, even by a single operator. The performance of this radar was tested in a controlled environment and in a realistic case study.
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4

Zheng, Xiangtian, Xiaolin Yang, Haitao Ma, Guiwen Ren, Keli Zhang, Feng Yang, and Ce Li. "Integrated Ground-Based SAR Interferometry, Terrestrial Laser Scanner, and Corner Reflector Deformation Experiments." Sensors 18, no. 12 (December 12, 2018): 4401. http://dx.doi.org/10.3390/s18124401.

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An integrated sensor system comprised of a terrestrial laser scanner (TLS), corner reflectors (CRs), and high precision linear rail is utilized to validate ground-based synthetic aperture radar (GB-SAR) interferometric micro-displacement measurements. A rail with positioning accuracy of 0.1 mm is deployed to ensure accurate and controllable deformation. The rail is equipped with a CR on a sliding platform for mobility. Three smaller CRs are installed nearby, each with a reflective sticker attached to the CR’s vertex; the CRs present as high-amplitude points both in the GB-SAR images and the TLS point cloud to allow for accurate data matching. We analyze the GB-SAR zero-baseline repeated rail differential interferometry signal model to obtain 2D interferograms of the test site in time series, and then use TLS to obtain a 3D surface model. The model is matched with interferograms to produce more intuitive 3D products. The CR displacements can also be extracted via surface reconstruction algorithm. Finally, we compared the rail sensor measurement and TLS results to optimize coherent scatterer selection and filter the data. The proposed method yields accurate target displacement results via quantitative analysis of GB-SAR interferometry.
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5

Wang, Peng, Cheng Xing, and Xiandong Pan. "Reservoir Dam Surface Deformation Monitoring by Differential GB-InSAR Based on Image Subsets." Sensors 20, no. 2 (January 10, 2020): 396. http://dx.doi.org/10.3390/s20020396.

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Ground-based synthetic aperture radar interferometry (GB-InSAR) enables the continuous monitoring of areal deformation and can thus provide near-real-time control of the overall deformation state of dam surfaces. In the continuous small-scale deformation monitoring of a reservoir dam structure by GB-InSAR, the ground-based synthetic aperture radar (GB-SAR) image acquisition may be interrupted by multiple interfering factors, such as severe changes in the meteorological conditions of the monitoring area and radar equipment failures. As a result, the observed phases before and after the interruption cannot be directly connected, and the original spatiotemporal datum for the deformation measurement is lost, making the follow-up monitoring results unreliable. In this study, a multi-threshold strategy was first adopted to select coherent point targets (CPTs) by using successive GB-SAR image sequences. Then, we developed differential GB-InSAR with image subsets based on the CPTs to solve the dam surface deformation before and after aberrant interruptions. Finally, a deformation monitoring experiment was performed on an actual large reservoir dam. The effectiveness and accuracy of the abovementioned method were verified by comparing the results with measurements by a reversed pendulum monitoring system.
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6

Huang, Zengshu, Jinping Sun, Qing Li, Weixian Tan, Pingping Huang, and Yaolong Qi. "Time- and Space-Varying Atmospheric Phase Correction in Discontinuous Ground-Based Synthetic Aperture Radar Deformation Monitoring." Sensors 18, no. 11 (November 11, 2018): 3883. http://dx.doi.org/10.3390/s18113883.

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Ground-based synthetic aperture radar (GB-SAR) uses active microwave remote-sensing observation mode to achieve two-dimensional deformation measurement and deformation trend extraction, which shows great prospects in the field of deformation monitoring. However, in the process of GB-SAR deformation monitoring, the disturbances caused by atmospheric effect cannot be neglected, and the atmospheric phases will seriously affect the precision of deformation monitoring. In discontinuous GB-SAR deformation monitoring mode, the atmospheric phases are particularly affected by changes of time and space, so the traditional models of atmospheric phase correction are no longer applicable. In this paper, the interferometric phase signal model considering atmospheric phase is first established. Then, the time- and space-varying characteristics of the atmospheric phase are analyzed, and a novel time- and space-varying atmospheric phase correction algorithm, based on coherent scatterers analysis, is proposed. Finally, slope deformation monitoring experiments are carried out to verify the validity and robustness of the proposed algorithm.
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7

Crosetto, M., O. Monserrat, G. Luzi, N. Devanthéry, M. Cuevas-González, and A. Barra. "DATA PROCESSING AND ANALYSIS TOOLS BASED ON GROUND-BASED SYNTHETIC APERTURE RADAR IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7 (September 13, 2017): 593–96. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w7-593-2017.

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The Ground-Based SAR (GBSAR) is a terrestrial remote sensing technique used to measure and monitor deformation. In this paper we describe two complementary approaches to derive deformation measurements using GBSAR data. The first approach is based on radar interferometry, while the second one exploits the GBSAR amplitude. In this paper we consider the so-called discontinuous GBSAR acquisition mode. The interferometric process is not always straightforward: it requires appropriate data processing and analysis tools. One of the main critical steps is phase unwrapping, which can critically affect the deformation measurements. In this paper we describe the procedure used at the CTTC to process and analyse discontinuous GBSAR data. In the second part of the paper we describe the approach based on GBSAR amplitude images and an image-matching method.
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8

Xu, Bing, Zhiwei Li, Yan Zhu, Jiancun Shi, and Guangcai Feng. "SAR Interferometric Baseline Refinement Based on Flat-Earth Phase without a Ground Control Point." Remote Sensing 12, no. 2 (January 9, 2020): 233. http://dx.doi.org/10.3390/rs12020233.

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Interferometric baseline estimation is a key procedure of interferometric synthetic aperture radar (SAR) data processing. The error of the interferometric baseline affects not only the removal of the flat-earth phase, but also the transformation coefficient between the topographic phase and elevation, which will affect the topographic phase removal for differential interferometric SAR (D-InSAR) and the accuracy of the final generated digital elevation model (DEM) product for interferometric synthetic aperture (InSAR). To obtain a highly accurate interferometric baseline, this paper firstly investigates the geometry of InSAR imaging and establishes a rigorous relationship between the interferometric baseline and the flat-earth phase. Then, a baseline refinement method without a ground control point (GCP) is proposed, where a relevant theoretical model and resolving method are developed. Synthetic and real SAR datasets are used in the experiments, and a comparison with the conventional least-square (LS) baseline refinement method is made. The results demonstrate that the proposed method exhibits an obvious improvement over the conventional LS method, with percentages of up to 51.5% in the cross-track direction. Therefore, the proposed method is effective and advantageous.
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9

Palamà, R., M. Crosetto, O. Monserrat, A. Barra, B. Crippa, M. Mróz, N. Kotulak, M. Mleczko, and J. Rapinski. "ANALYSIS OF MINING-INDUCED TERRAIN DEFORMATION USING MULTITEMPORAL DISTRIBUTED SCATTERER SAR INTERFEROMETRY." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2022 (May 30, 2022): 321–26. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2022-321-2022.

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Abstract. This work addresses a methodology based on the Interferometric Synthetic Aperture Radar (InSAR) to analyse and monitor ground motion phenomena induced by underground mining activities, in the Legnica-Glogow Copper District, south-western Poland. Two stacks of ascending and descending Sentinel-1 Synthetic Aperture Radar (SAR) images are processed with a small baseline multitemporal approach. A simple method to select interferograms with high coherence and eliminated images with low redundancy is implemented to optimize the interferogram netwrork. The estimated displacement maps and time series show the effect of both linear and impulsive ground motion and are validated against Global Navigation Satellite System (GNSS) measurements.
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10

Guo, Yanhui, Zhiquan Yang, Yi Yang, Zhijun Kong, Caikun Gao, and Weiming Tian. "Experimental Study on Deformation Monitoring of Large Landslide in Reservoir Area of Hydropower Station Based on GB-InSAR." Advances in Civil Engineering 2021 (July 8, 2021): 1–11. http://dx.doi.org/10.1155/2021/5586340.

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The monitoring and early warning of a landslide in the reservoir area of a hydropower station are of great significance in the dam structure of the hydropower station and in the safety of people’s life and property on the reservoir bank. In this study, a new ground-based interferometric synthetic aperture radar system LKR-05-KU-S100 was used to carry out field monitoring tests on Lagu landslide and Xiaozhaju landslide of Dahuaqiao hydropower station and No. 1 landslide on the left bank of Xiaowan hydropower station on the Lancang river. The results show that, during the monitoring period, Lagu landslide of Dahuaqiao hydropower station and No. 1 landslide on the left bank of Xiaowan hydropower station are basically stable, and the deformation trend of Xiaozhaju landslide is obvious so it should undergo continuous monitoring. At the same time, the field monitoring test also shows that the new ground-based interferometric synthetic aperture radar system LKR-05-KU-S100 has the advantages of high precision and long-distance, all-day, all-weather, and large-scale monitoring and has unique advantages and broad application prospects for the overall deformation monitoring of large landslides in the reservoir area.
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11

Li, Bing, Zemin Wang, Jiachun An, Baojun Zhang, Hong Geng, Yuanyuan Ma, Mingci Li, and Yide Qian. "Ionospheric Phase Compensation for InSAR Measurements Based on the Faraday Rotation Inversion Method." Sensors 20, no. 23 (December 1, 2020): 6877. http://dx.doi.org/10.3390/s20236877.

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The ionospheric error can significantly affect the synthetic aperture radar (SAR) signals, particularly in the case of L band and lower frequency SAR systems. The ionospheric distortions are mixed with terrain and ground deformation signals, lowering the precision of the interferometric measurements. Moreover, it is often difficult to detect the small-scale ionospheric structure due to its rapid changes and may have more influence on ionospheric phase compensation for InSAR measurements. In this paper, we present a Faraday rotation (FR) inversion method and corresponding procedure to compensate the ionospheric error for SAR interferograms and to detect the variations of small-scale ionospheric disturbances. This method retrieves the absolute total electron content (TEC) based on the FR estimation and corrects the ionospheric error for synthetic aperture radar interferometry (InSAR) measurements by transforming the differential TEC into the ionospheric phase. In two selected study cases, located in high latitude and equatorial regions where ionospheric disturbances occur frequently, we test the method using the Phased Array L-band Synthetic Aperture Radar (PALSAR) full-polarimetric SAR images. Our results show that the proposed procedure can effectively compensate the ionospheric phase. In order to validate the results, we present the results of ionospheric phase compensation based on the split-spectrum method as a comparison to the proposed method. To analyze the ability of our proposed method in detecting small-scale ionospheric disturbances, TEC derived from FR estimation are also compared with those derived from the global ionosphere maps (GIM). Our research provides a robust choice for the correction of ionospheric error in SAR interferograms. It also provides a powerful tool to measure small-scale ionospheric structure.
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12

Monserrat, O., J. Moya, G. Luzi, M. Crosetto, J. A. Gili, and J. Corominas. "Non-interferometric GB-SAR measurement: application to the Vallcebre landslide (eastern Pyrenees, Spain)." Natural Hazards and Earth System Sciences 13, no. 7 (July 29, 2013): 1873–87. http://dx.doi.org/10.5194/nhess-13-1873-2013.

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Abstract. In the last decade, ground-based interferometry has proven to be a powerful technique for continuous deformation monitoring of landslides, glaciers, volcanoes, or manmade structures, among others. However, several limitations need to be addressed in order to improve the performances of the technique, especially for long-term monitoring. These limitations include the reduction of measurable points with an increase in the period of observation, the ambiguous nature of the phase measurements, and the influence of the atmospheric phase component. In this paper, a new procedure to process the amplitude component of ground-based synthetic aperture radar (GB-SAR) data acquired in discontinuous mode is compared and validated. The use of geometric features of the amplitude images combined with a matching technique will allow the estimation of the displacements over specific targets. Experimental results obtained during 19 months, in eight different campaigns carried out in the active landslide of Vallcebre (eastern Pyrenees, Spain), were analysed. During the observed period, from February 2010 to September 2011, displacements up to 80 cm were measured. The comparison with other surveying technique shows that the precision of the method is below 1 cm.
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13

Cai, Jialun, Hongguo Jia, Guoxiang Liu, Bo Zhang, Qiao Liu, Yin Fu, Xiaowen Wang, and Rui Zhang. "An Accurate Geocoding Method for GB-SAR Images Based on Solution Space Search and Its Application in Landslide Monitoring." Remote Sensing 13, no. 5 (February 24, 2021): 832. http://dx.doi.org/10.3390/rs13050832.

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Although ground-based synthetic aperture radar (GB-SAR) interferometry has a very high precision with respect to deformation monitoring, it is difficult to match the fan-shaped grid coordinates with the local topography in the geographical space because of the slant range projection imaging mode of the radar. To accurately identify the deformation target and its position, high-accuracy geocoding of the GB-SAR images must be performed to transform them from the two-dimensional plane coordinate system to the three-dimensional (3D) local coordinate system. To overcome difficulties of traditional methods with respect to the selection of control points in GB-SAR images in a complex scattering environment, a high-resolution digital surface model obtained by unmanned aerial vehicle (UAV) aerial photogrammetry was used to establish a high-accuracy GB-SAR coordinate transformation model. An accurate GB-SAR image geocoding method based on solution space search was proposed. Based on this method, three modules are used for geocoding: framework for the unification of coordinate elements, transformation model, and solution space search of the minimum Euclidean distance. By applying this method to the Laoguanjingtai landslide monitoring experiment on Hailuogou Glacier, a subpixel geocoding accuracy was realized. The effectiveness and accuracy of the proposed method were verified by contrastive analysis and error assessment. The method proposed in this study can be applied for accurate 3D interpretation and analysis of the spatiotemporal characteristic in GB-SAR deformation monitoring and should be popularized.
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Ozawa, Taku, Yuji Himematsu, Akira Nohmi, and Masanori Miyawaki. "Development of Portable SAR for Detection of Volcano Deformation: Application of SAR Interferometry to the Repeated Observation Data." Journal of Disaster Research 17, no. 5 (August 1, 2022): 609–19. http://dx.doi.org/10.20965/jdr.2022.p0609.

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Synthetic aperture radar (SAR), which transmits radar waves from the ground, can detect crustal deformation with high spatial and temporal resolution. To obtain crustal deformation data useful for evaluating volcanic activity, we are developing a portable SAR that can conduct repeated observations without being fixed to the site under Project B of the Integrated Program for Next Generation Volcano Research and Human Resource Development. We named this SAR sensor: SAR for crustal deformation with portable equipment (SCOPE). SCOPE detects crustal deformation over a wide area by repeating observations at several points, which differs from the general ground-based SAR (GB-SAR). SCOPE has four observation types: GB-SAR, car-borne SAR, cart-borne SAR, and man-borne SAR, which are used to conduct such mobile observations efficiently. This study performed repeated observations with a 1-day interval using GB-SAR and car-borne SAR and obtained high coherence and reasonable phase distribution. When using the man-borne SAR type, moderate coherence was obtained. However, focusing on the SAR image was insufficient, and an inappropriate phase slope appeared in the interferogram, suggesting that improvements in the observation and analysis methods remained. We also investigated the temporal persistence of coherence when applying SAR interferometry to the SCOPE data. Sufficient coherence was obtained to detect crustal deformation in sparsely vegetated areas for a data pair at a 1-year interval. Even in densely vegetated areas, sufficient coherence was obtained from the data pair at intervals of several months. These results show that SCOPE has high potential for detecting crustal deformation based on repeated observations.
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Chojka, Agnieszka, Piotr Artiemjew, and Jacek Rapiński. "RFI Artefacts Detection in Sentinel-1 Level-1 SLC Data Based On Image Processing Techniques." Sensors 20, no. 10 (May 21, 2020): 2919. http://dx.doi.org/10.3390/s20102919.

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Interferometric Synthetic Aperture Radar (InSAR) data are often contaminated by Radio-Frequency Interference (RFI) artefacts that make processing them more challenging. Therefore, easy to implement techniques for artefacts recognition have the potential to support the automatic Permanent Scatterers InSAR (PSInSAR) processing workflow during which faulty input data can lead to misinterpretation of the final outcomes. To address this issue, an efficient methodology was developed to mark images with RFI artefacts and as a consequence remove them from the stack of Synthetic Aperture Radar (SAR) images required in the PSInSAR processing workflow to calculate the ground displacements. Techniques presented in this paper for the purpose of RFI detection are based on image processing methods with the use of feature extraction involving pixel convolution, thresholding and nearest neighbor structure filtering. As the reference classifier, a convolutional neural network was used.
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Rebmeister, M., A. Schenk, and S. Hinz. "COMPARISON AND EVALUATION OF DIFFERENT APPROACHES FOR EFFICIENT PROCESSING OF LONG GROUND-BASED SAR TIMES SERIES." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2022 (May 30, 2022): 341–48. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2022-341-2022.

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Abstract. Ground-based Synthetic Aperture Radar (GB-SAR) is a monitoring tool which, once installed, acquires a large amount of data autonomously. For the IBIS-FM system, approximately 760 SAR images per day are acquired, which corresponds to more than 23 000 scenes per month. Therefore, this paper analysis different strategies for the interferometric processing of such large data stacks to find a compromise between accuracy, computational effort and the ability to (re-)process specific time intervals independently. This study compares the single master approach with the sequential approach and in addition two block-wise approaches. Moreover, a new baseline configuration called Daily Baseline Subset (DBAS) is compared which uses interferograms having a multiple of one day as temporal baseline. We evaluate them on a data stack of 30 000 images, acquired at Enguri Dam in Georgia. We check the unwrapping errors and the quality of the displacement estimation to compare the different configurations. We found that block-wise approaches show the best results considering unwrapping errors and Root Mean Square Error, while in our study the DBAS approach shows to the most plausible displacement map which is also dependent on the individual reduction of atmospheric noise.
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Ito, Y., H. Ikemitsu, and K. Nango. "DEVELOPMENT AND EVALUATION OF SCIENCE AND TECHNOLOGY EDUCATION PROGRAM USING INTERFEROMETRIC SAR." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B6 (June 17, 2016): 123–29. http://dx.doi.org/10.5194/isprs-archives-xli-b6-123-2016.

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This paper proposes a science and technology education program to teach junior high school students to measure terrain changes by using interferometric synthetic aperture radar (SAR). The objectives of the proposed program are to evaluate and use information technology by performing SAR data processing in order to measure ground deformation, and to incorporate an understanding of Earth sciences by analyzing interferometric SAR processing results. To draft the teaching guidance plan for the developed education program, this study considers both science and technology education. The education program was used in a Japanese junior high school. An educational SAR processor developed by the authors and the customized Delft object-oriented radar interferometric software package were employed. Earthquakes as diastrophism events were chosen as practical teaching materials. The selected events indicate clear ground deformation in differential interferograms with high coherence levels. The learners were able to investigate the ground deformations and disasters caused by the events. They interactively used computers and became skilled at recognizing the knowledge and techniques of information technology, and then they evaluated the technology. Based on the results of pre- and post-questionnaire surveys and self-evaluation by the learners, it was clarified that the proposed program was applicable for junior high school education, and the learners recognized the usefulness of Earth observation technology by using interferometric SAR. The usefulness of the teaching materials in the learning activities was also shown through the practical teaching experience.
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Ito, Y., H. Ikemitsu, and K. Nango. "DEVELOPMENT AND EVALUATION OF SCIENCE AND TECHNOLOGY EDUCATION PROGRAM USING INTERFEROMETRIC SAR." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B6 (June 17, 2016): 123–29. http://dx.doi.org/10.5194/isprsarchives-xli-b6-123-2016.

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This paper proposes a science and technology education program to teach junior high school students to measure terrain changes by using interferometric synthetic aperture radar (SAR). The objectives of the proposed program are to evaluate and use information technology by performing SAR data processing in order to measure ground deformation, and to incorporate an understanding of Earth sciences by analyzing interferometric SAR processing results. To draft the teaching guidance plan for the developed education program, this study considers both science and technology education. The education program was used in a Japanese junior high school. An educational SAR processor developed by the authors and the customized Delft object-oriented radar interferometric software package were employed. Earthquakes as diastrophism events were chosen as practical teaching materials. The selected events indicate clear ground deformation in differential interferograms with high coherence levels. The learners were able to investigate the ground deformations and disasters caused by the events. They interactively used computers and became skilled at recognizing the knowledge and techniques of information technology, and then they evaluated the technology. Based on the results of pre- and post-questionnaire surveys and self-evaluation by the learners, it was clarified that the proposed program was applicable for junior high school education, and the learners recognized the usefulness of Earth observation technology by using interferometric SAR. The usefulness of the teaching materials in the learning activities was also shown through the practical teaching experience.
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Zhao, Yuan, Nicolas Longépé, Alexis Mouche, and Romain Husson. "Automated Rain Detection by Dual-Polarization Sentinel-1 Data." Remote Sensing 13, no. 16 (August 10, 2021): 3155. http://dx.doi.org/10.3390/rs13163155.

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Rain Signatures on C-band Synthetic Aperture Radar (SAR) images acquired over ocean are common and can dominate the backscattered signal from the ocean surface. In many cases, the inability to decipher between ocean and rain signatures can disturb the analysis of SAR scenes for maritime applications. This study relies on Sentinel-1 SAR acquisitions in the Interferometric Wide swath mode and high-resolution measurements from ground-based weather radar to document the rain impact on the radar backscattered signal in both co- and cross-polarization channels. The dark and bright rain signatures are found in connection with the timeliness of the rain cells. In particular, the bright patches are demonstrated by the hydrometeors (graupels, hails) in the melting layer. In general, the radar backscatter under rain increases with rain rate for a given sea state and decreases when the sea state strengthens. The rain also has a stronger impact on the radar signal in both polarizations when the incidence angle increases. The complementary sensitivity of the SAR signal of rain in both channels is then used to derive a filter to locate the areas in SAR scenes where the signal is not dominated by rain. The filter optimized to match the rain observed by the ground-based weather radar is more efficient when both polarization channels are considered. Case studies are presented to discuss the advantages and limitations of such a filtering approach.
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Huang Lin, Liu, and Liu. "Landslide detection in La Paz City (Bolivia) based on time series analysis of InSAR data." International Journal of Remote Sensing 40, no. 17 (September 2, 2019): 6775–95. http://dx.doi.org/10.1080/01431161.2019.1594434.

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Geologically, La Paz City is located in an unstable area. During the history of La Paz city, many landslides have destroyed houses and valuable infrastructures. In the last decades, time series Interferometric Synthetic Aperture Radar (InSAR) technologies have demonstrated a great capacity for detecting slow ground displacement, achieving an accuracy of millimetre-level. In order to have a better landslide monitoring of La Paz city, in this study, the Sentinel-1 SAR images have been processed by Persistent Scatterer Interferometry (PSI) and the Small Baseline Subset (SBAS) techniques. The time span of the datasets is from March 2015 to August 2016. Both ascending and descending Synthetic Aperture Radar (SAR) images have been processed to obtain the line of sight (LOS) ground velocity, and then the results have been combined to estimate the up-down and east-west displacement. Several active movement areas have been identified, showing a surface velocity up to 158 mm year−1 westward and 49 mm year−1 eastward. Furthermore, two important findings have been discovered. First, the InSAR result has detected movement in Auquisamaa hill before the area collapsed (15 February 2017), where five houses are buried. Second, the InSAR result has identified that there are still some unstable sites in Callapa area, where a mega-landslide has destroyed more than a thousand of houses in February 2011. In conclusion, we have verified that the InSAR technology could be a very useful tool to help La Paz public institutions for a better management of urban planning, landslide areas delimitation and landslide risk mitigation.
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Palamà, Riccardo, Michele Crosetto, Jacek Rapinski, Anna Barra, María Cuevas-González, Oriol Monserrat, Bruno Crippa, Natalia Kotulak, Marek Mróz, and Magdalena Mleczko. "A Multi-Temporal Small Baseline Interferometry Procedure Applied to Mining-Induced Deformation Monitoring." Remote Sensing 14, no. 9 (May 2, 2022): 2182. http://dx.doi.org/10.3390/rs14092182.

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This work addresses a methodology based on the interferometric synthetic aperture radar (InSAR) applied to analyze and monitor ground-motion phenomena induced by underground mining activities in the Legnica-Glogow copper district, south-western Poland. The adopted technique employs an InSAR processing chain that exploits a stack of Sentinel-1 synthetic aperture radar (SAR) images using a small baseline multitemporal approach. Interferograms with small temporal baselines are first selected, then their network is optimized and reduced to eliminate noisy data, in order to mitigate the effect of decorrelation sources related to seasonal phenomena, i.e., snow and vegetation growth, and to the radar acquisition geometry. The atmospheric disturbance is mitigated using a spatio-temporal filter based on the nonequispaced fast Fourier transform. The estimated displacement maps and time series show the effect of both linear and impulsive ground motion and are validated against global navigation satellite system (GNSS) measurements. In this context, a significant threat to the built environment is represented by seismic tremors triggered by underground mining activities, which are analyzed using the proposed method to integrate the information gathered by in situ seismometer devices.
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Crosetto, M., L. Solari, J. Balasis-Levinsen, L. Bateson, N. Casagli, M. Frei, A. Oyen, D. A. Moldestad, and M. Mróz. "DEFORMATION MONITORING AT EUROPEAN SCALE: THE COPERNICUS GROUND MOTION SERVICE." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2021 (June 28, 2021): 141–46. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2021-141-2021.

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Abstract. The Advanced Differential Interferometric SAR (A-DInSAR) technique is a class of powerful techniques to monitor ground motion. In the last two decades, the A-DInSAR technique has undergone an important development in terms of processing algorithms and the capability to monitor wide areas. This has been accompanied by an important increase of the Synthetic Aperture Radar (SAR) data acquisition capability by spaceborne sensors. An important step forward was the launch of the Copernicus Sentinel-1 constellation. The development of A-DInSAR based ground deformation services is now technically feasible. This paper describes some of the most important features of A-DInSAR. Then, it describes the European Ground Motion Service (EGMS), part of the Copernicus Land Monitoring Service, which represents a unique initiative for performing ground deformation monitoring on a European scale.
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Chen, Yafeng, Da Liang, Haixia Yue, Dacheng Liu, Xiayi Wu, Heng Zhang, Yuanbo Jiao, Kaiyu Liu, and Robert Wang. "Implementation of a Phase Synchronization Scheme Based on Pulsed Signal at Carrier Frequency for Bistatic SAR." Sensors 20, no. 11 (June 4, 2020): 3188. http://dx.doi.org/10.3390/s20113188.

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Phase synchronization is one of the key technical challenges and prerequisites for the bistatic synthetic aperture radar (SAR) system, which can form a single-pass interferometry system to perform topographic mapping. In this paper, an advanced phase synchronization scheme based on a pulsed signal at carrier frequency is proposed for a bistatic SAR system and it is verified by a ground validation system. In the proposed phase synchronization scheme, the pulsed signal at carrier frequency is used for phase synchronization link, and it is exchanged by virtue of a time slot between radar signals. The feasibility of the scheme is proven by theoretical analysis of various factors affecting the performance of phase synchronization, and the reliability of the scheme is verified by the test results of the ground validation system.
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Polcari, Marco, Matteo Albano, Antonio Montuori, Christian Bignami, Cristiano Tolomei, Giuseppe Pezzo, Sergio Falcone, et al. "InSAR Monitoring of Italian Coastline Revealing Natural and Anthropogenic Ground Deformation Phenomena and Future Perspectives." Sustainability 10, no. 9 (September 4, 2018): 3152. http://dx.doi.org/10.3390/su10093152.

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In this work, we use X and C-band SAR data provided by the COSMO-SkyMed and ENVISAT missions to detect and measure some ground deformation phenomena along six coastal areas of Italy. In particular, we exploit multi-temporal interferometric synthetic aperture radar (InSAR), i.e., small baseline subsets (SBAS) and interferometric point target analysis (IPTA) methods, to retrieve the deformation rate maps and time series for each investigated area. Multi-temporal InSAR analysis revealed local subsidence and uplifting effects in Ravenna Coastal Areas, Fiumicino, Campi Flegrei, Sibari Plain, Augusta Bay, and Taranto Gulf. Our work is meant as a demonstrator to show how InSAR-based analysis can provide a detailed understanding of the coastal hazards. Such analysis also opens up new monitoring scenarios such as the possibility of designing a near real-time surveillance service based on Sentinel-1 SAR data.
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Chen, Wei, Qihui Zheng, Haibing Xiang, Xu Chen, and Tetsuro Sakai. "Forest Canopy Height Estimation Using Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) Technology Based on Full-Polarized ALOS/PALSAR Data." Remote Sensing 13, no. 2 (January 6, 2021): 174. http://dx.doi.org/10.3390/rs13020174.

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Forest canopy height is a basic metric characterizing forest growth and carbon sink capacity. Based on full-polarized Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar (ALOS/PALSAR) data, this study used Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) technology to estimate forest canopy height. In total the four methods of differential DEM (digital elevation model) algorithm, coherent amplitude algorithm, coherent phase-amplitude algorithm and three-stage random volume over ground algorithm (RVoG_3) were proposed to obtain canopy height and their accuracy was compared in consideration of the impacts of coherence coefficient and range slope levels. The influence of the statistical window size on the coherence coefficient was analyzed to improve the estimation accuracy. On the basis of traditional algorithms, time decoherence was performed on ALOS/PALSAR data by introducing the change rate of Landsat NDVI (Normalized Difference Vegetation Index). The slope in range direction was calculated based on SRTM (Shuttle Radar Topography Mission) DEM data and then introduced into the s-RVoG (sloped-Random Volume over Ground) model to optimize the canopy height estimation model and improve the accuracy. The results indicated that the differential DEM algorithm underestimated the canopy height significantly, while the coherent amplitude algorithm overestimated the canopy height. After removing the systematic coherence, the overestimation of the RVoG_3 model was restrained, and the absolute error decreased from 23.68 m to 4.86 m. With further time decoherence, the determination coefficient increased to 0.2439. With the introduction of range slope, the s-RVoG model shows improvement compared to the RVoG model. Our results will provide a reference for the appropriate algorithm selection and optimization for forest canopy height estimation using full-polarized L-band synthetic aperture radar (SAR) data for forest ecosystem monitoring and management.
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Tian, Weiming, Zheng Zhao, Cheng Hu, Jingyang Wang, and Tao Zeng. "GB-InSAR-Based DEM Generation Method and Precision Analysis." Remote Sensing 11, no. 9 (April 26, 2019): 997. http://dx.doi.org/10.3390/rs11090997.

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Ground-based interferometric technology plays an important role in the terrain mapping sphere because it is characterized by short observation intervals, a flexible operation environment, and high data precision. Ground-based interferometric synthetic aperture radar (GB-InSAR) has a wide beam, a scene breadth comparative to the slant range, and a large downwards-looking angle. The observation scenes always show the type of slope terrain with various gradients and slope orientations. These particularities cause the invalidation of the typical terrain generation method and produce poor precision analysis results using typical values. This paper first proposes a three-dimensional-coordinate generation method based on the geolocation concept. Then, the models and analyses of the error sources and their propagations are reported. The method of calculating the correlation coefficient is meticulously discussed, and a system error distribution diagram is presented that considers the spatial distribution information of the viewing scene. The result can be adapted to different viewing scenes and encompasses the performance of the whole area, and it will help with baseline optimization. The digital elevation map (DEM) generated by GB-InSAR is compared with one produced by light detection and ranging (LiDAR). The error magnitude and the similarity of the distribution between theory and reality prove the correctness and effectiveness of the presented DEM generation method, the correlation coefficient estimation formula, and the system precision analysis method.
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Nico, Giovanni, Sérgio Oliveira, Joao Catalão, and José Zêzere. "Generation of Persistent Scatterers in Non-Urban Areas: The Role of Microwave Scattering Parameters." Geosciences 8, no. 7 (July 23, 2018): 269. http://dx.doi.org/10.3390/geosciences8070269.

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In this work, we study the capability of the ground surface to generate Persistent Scatterers (PS) based on the lithology, slope and aspect angles. These properties affect the scattering behavior of the Synthetic Aperture Radar (SAR) signal, the interferometric phase stability and, as a consequence, the PS generation. Two-time series of interferometric SAR data acquired by two different SAR sensors in the C-band are processed to generate independent PS datasets. The region north of Lisbon, Portugal, characterized by sparse vegetation and lithology diversity, is chosen as study area. The PS frequency distribution is obtained in terms of lithology, slope and aspect angles. This relationship could be useful to estimate the expected PS density in landslide-prone areas, being lithology, slope and aspect angles important landslide predisposing factors.
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Del Ventisette, C., E. Intrieri, G. Luzi, N. Casagli, R. Fanti, and D. Leva. "Using ground based radar interferometry during emergency: the case of the A3 motorway (Calabria Region, Italy) threatened by a landslide." Natural Hazards and Earth System Sciences 11, no. 9 (September 22, 2011): 2483–95. http://dx.doi.org/10.5194/nhess-11-2483-2011.

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Abstract. The rapid assessment of the evolution of the phenomena which occur during an emergency, along with an all weather and h24 monitoring capability, are probably the main characteristics of a system aimed at optimizing intervention in natural disasters, such as landslide collapses. A few techniques are able to provide all these features remotely, hence assuring safe conditions to operators. This paper reports on an application of the GB-InSAR (Ground-Based Interferometric Synthetic Aperture Radar) technique to monitor a landslide threatening an infrastructure, the A3 motorway in the Calabria Region (Southern Italy), in emergency conditions. Here, it is evaluated how well this technique is able to satisfy these requirements. On 30 January 2009, a mass movement never detected before and located near Santa Trada viaduct caused the closure of that sector of the A3 motorway. The prompt installation of a GB-InSAR permitted to follow and to understand the temporal evolution of the landslide until the end of the emergency and then safely reopen of the motorway. The main steps of the GB-InSAR interferometry data interpretation used in managing this emergency are described and discussed here. In detail, data collected through a continuous acquisition have permitted the division of the unstable area into three smaller zones characterized by different extents of displacement.
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Milczarek, Wojciech, Anna Kopeć, Dariusz Głąbicki, and Natalia Bugajska. "Induced Seismic Events—Distribution of Ground Surface Displacements Based on InSAR Methods and Mogi and Yang Models." Remote Sensing 13, no. 8 (April 9, 2021): 1451. http://dx.doi.org/10.3390/rs13081451.

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In this article, we present a possible approach to use satellite radar data for a complete description of the formation process of a subsidence trough resulting from an induced seismic event—a mining tremor. Our main goal was to verify whether SAR data allow for the calculation of the basic indicators for the trough (w—subsidence, T—trough slope, K—curvature, u—horizontal displacements, ε—horizontal deformations). We verified the extent to which the Mogi and Yang models can be fitted to match the actual displacements recorded after an induced seismic tremor. The calculations were performed for the Legnica-Glogow Copper Belt (LGCB) area in southwest Poland. Due to intensive mining operations and specific geological and tectonic conditions, the area shows a high level of induced seismic activity. Our detailed analysis focused on four powerful mining tremors: the first tremor occurred on 29 November 2016 (MW3.4), the second on 7 December 2017 (MW3.3), the next on 26 December 2017 (MW3.6) and the last tremor on 29 January 2019 (MW3.7). For each analyzed event, we determined the displacements based on the Differential Interferometric Synthetic Aperture Radar (DInSAR) method and Sentinel 1 synthetic aperture radar (SAR) data from two paths (22 and 73). Additionally, for the period from November 2014 to October 2020, we calculated the displacements using the Small Baseline Subset method (SBAS) time series method. In all cases, the tremor was followed by the development of long-lasting surface deformations. The obtained results allowed us to conclude that it is possible to calculate indicators that result from a specific induced mining event. Considering the full moment tensor and nature of the tremor source, we demonstrated that the Mogi and Yang models can be employed to describe the influence of an induced tremor on the surface in an area of mining activity. We also confirmed the global character of the influence of the reduced troposphere on SAR data calculations. Our conclusions indicate that accounting for the tropospheric correction does not distort horizontal and vertical displacement values in regions influenced by mining activity/tremors.
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Han, Jianfeng, Honglei Yang, Youfeng Liu, Zhaowei Lu, Kai Zeng, and Runcheng Jiao. "A Deep Learning Application for Deformation Prediction from Ground-Based InSAR." Remote Sensing 14, no. 20 (October 11, 2022): 5067. http://dx.doi.org/10.3390/rs14205067.

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Ground-based synthetic aperture radar interferometry (GB-InSAR) has the characteristics of high precision, high temporal resolution, and high spatial resolution, and is widely used in highwall deformation monitoring. The traditional GB-InSAR real-time processing method is to process the whole data set or group in time sequence. This type of method takes up a lot of computer memory, has low efficiency, cannot meet the timeliness of slope monitoring, and cannot perform deformation prediction and disaster warning forecasting. In response to this problem, this paper proposes a GB-InSAR time series processing method based on the LSTM (long short-term memory) model. First, according to the early monitoring data of GBSAR equipment, the time series InSAR method (PS-InSAR, SBAS, etc.) is used to obtain the initial deformation information. According to the deformation calculated in the previous stage and the atmospheric environmental parameters monitored, the LSTM model is used to predict the deformation and atmospheric delay at the next time. The phase is removed from the interference phase, and finally the residual phase is unwrapped using the spatial domain unwrapping algorithm to solve the residual deformation. The predicted deformation and the residual deformation are added to obtain the deformation amount at the current moment. This method only needs to process the difference map at the current moment, which greatly saves time series processing time and can realize the prediction of deformation variables. The reliability of the proposed method is verified by ground-based SAR monitoring data of the Guangyuan landslide in Sichuan Province.
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Darvishi, Mehdi, Romy Schlögel, Christian Kofler, Giovanni Cuozzo, Martin Rutzinger, Thomas Zieher, Isabella Toschi, et al. "Sentinel-1 and Ground-Based Sensors for Continuous Monitoring of the Corvara Landslide (South Tyrol, Italy)." Remote Sensing 10, no. 11 (November 10, 2018): 1781. http://dx.doi.org/10.3390/rs10111781.

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The Copernicus Sentinel-1 mission provides synthetic aperture radar (SAR) acquisitions over large areas with high temporal and spatial resolution. This new generation of satellites providing open-data products has enhanced the capabilities for continuously studying Earth surface changes. Over the past two decades, several studies have demonstrated the potential of differential synthetic aperture radar interferometry (DInSAR) for detecting and quantifying land surface deformation. DInSAR limitations and challenges are linked to the SAR properties and the field conditions (especially in mountainous environments) leading to spatial and temporal decorrelation of the SAR signal. High temporal decorrelation can be caused by changes in vegetation (particularly in nonurban areas), atmospheric conditions, or high ground surface velocity. In this study, the kinematics of the complex and vegetated Corvara landslide, situated in Val Badia (South Tyrol, Italy), are monitored by a network of three permanent and 13 monthly measured benchmark points measured with the differential global navigation satellite system (DGNSS) technique. The slope displacement rates are found to be highly unsteady and reach several meters a year. This paper focuses firstly on evaluating the performance of DInSAR changing unwrapping and coherence parameters with Sentinel-1 imagery, and secondly, on applying DInSAR with DGNSS measurements to monitor an active and complex landslide. To this end, 41 particular SAR images, coherence thresholds, and 2D and 3D unwrapping processes give various results in terms of reliability and accuracy, supporting the understanding of the landslide velocity field. Evolutions of phase changes are analysed according to the coherence, the changing field conditions, and the monitored ground-based displacements.
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Xiao, Ting, Wei Huang, Yunkai Deng, Weiming Tian, and Yonglian Sha. "Long-Term and Emergency Monitoring of Zhongbao Landslide Using Space-Borne and Ground-Based InSAR." Remote Sensing 13, no. 8 (April 19, 2021): 1578. http://dx.doi.org/10.3390/rs13081578.

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This work presents the ideal combination of space-borne and ground-based (GB) Interferometric Synthetic Aperture Radar (InSAR) applications. In the absence of early investigation reporting and specialized monitoring, the Zhongbao landslide unexpectedly occurred on 25 July 2020, forming a barrier lake that caused an emergency. As an emergency measure, the GB-InSAR system was installed 1.8 km opposite the landslide to assess real-time cumulative deformation with a monitoring frequency of 3 min. A zone of strong deformation was detected, with 178 mm deformation accumulated within 15 h, and then a successful emergency warning was issued to evacuate on-site personnel. Post-event InSAR analysis of 19 images acquired by the ESA Sentinel-1 from December 2019 to August 2020 revealed that the landslide started in March 2020. However, the deformation time series obtained from satellite InSAR did not show any signs that the landslide had occurred. The results suggest that satellite InSAR is effective for mapping unstable areas but is not qualified for rapid landslide monitoring and timely warning. The GB-InSAR system performs well in monitoring and providing early warning, even with dense vegetation on the landslide. The results show the shortcomings of satellite InSAR and GB-InSAR and a clearer understanding of the necessity of combining multiple monitoring methods.
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Hawley, Robert L., Ola Brandt, Thorben Dunse, Jon Ove Hagen, Veit Helm, Jack Kohler, Kirsty Langley, Eirik Malnes, and Kjell-Arild Høgda. "Using airborne Ku-band altimeter waveforms to investigate winter accumulation and glacier facies on Austfonna, Svalbard." Journal of Glaciology 59, no. 217 (2013): 893–99. http://dx.doi.org/10.3189/2013jog13j051.

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AbstractWinter balance is an important metric for assessing the change on glaciers and ice caps, yet measuring it using ground-based techniques can be challenging. We use the European Space Agency prototype Airborne SAR/Interferometric Radar Altimeter System (ASIRAS) to extract snow depths from the received altimeter waveforms over Austfonna ice cap, Svalbard. Additionally, we attempt to distinguish the long-term firn area from other glacier facies. We validate our results using snow depth and glacier facies characterizations determined from ground-based radar profiles, snow pits and a multi-look satellite synthetic aperture radar image. We show that the depth of the winter snowpack can be extracted from the altimeter data over most of the accumulation zone, comprising wet snow zone and a superimposed ice zone. The method struggles at lower elevations where internal reflections within the winter snowpack are strong and the winter snow depth is less than ∼1 m. We use the abruptness of the reflection from the last summer surface (LSS) to attempt to distinguish glacier facies. While there is a general correlation between LSS abruptness and glacier facies, we do not find a relationship that warrants a distinct classification based on ASIRAS waveforms alone.
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Sun, Xinyao, Aaron Zimmer, Subhayan Mukherjee, Navaneeth Kamballur Kottayil, Parwant Ghuman, and Irene Cheng. "DeepInSAR—A Deep Learning Framework for SAR Interferometric Phase Restoration and Coherence Estimation." Remote Sensing 12, no. 14 (July 21, 2020): 2340. http://dx.doi.org/10.3390/rs12142340.

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Over the past decade, using Interferometric Synthetic Aperture Radar (InSAR) remote sensing technology for ground displacement detection has become very successful. However, during the acquisition stage, microwave signals reflected from the ground and received by the satellite are contaminated, for example, due to undesirable material reflectance and atmospheric factors, and there is no clean ground truth to discriminate these noises, which adversely affect InSAR phase computation. Accurate InSAR phase filtering and coherence estimation are crucial for subsequent processing steps. Current methods require expert supervision and expensive runtime to evaluate the quality of intermediate outputs, limiting the usability and scalability in practical applications, such as wide area ground displacement monitoring and predication. We propose a deep convolutional neural network based model DeepInSAR to intelligently solve both phase filtering and coherence estimation problems. We demonstrate our model’s performance using simulated and real data. A teacher-student framework is introduced to handle the issue of missing clean InSAR ground truth. Quantitative and qualitative evaluations show that our teacher-student approach requires less input but can achieve better results than its stack-based teacher method even on new unseen data. The proposed DeepInSAR also outperforms three other top non-stack based methods in time efficiency without human supervision.
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Bondur, Valery, Tumen Chimitdorzhiev, Aleksey Dmitriev, and Pavel Dagurov. "Fusion of SAR Interferometry and Polarimetry Methods for Landslide Reactivation Study, the Bureya River (Russia) Event Case Study." Remote Sensing 13, no. 24 (December 17, 2021): 5136. http://dx.doi.org/10.3390/rs13245136.

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In this paper, we demonstrate the estimation capabilities of landslide reactivation based on various SAR (Synthetic Aperture Radar) methods: Cloude-Pottier decomposition of Sentinel-1 dual polarimetry data, MT-InSAR (Multi-temporal Interferometric Synthetic Aperture Radar) techniques, and cloud computing of backscattering time series. The object of the study is the landslide in the east of Russia that took place on 11 December 2018 on the Bureya River. H-α-A polarimetric decomposition of C-band radar images not detected significant transformations of scattering mechanisms for the surface of the rupture, whereas L-band radar data show changes in scattering mechanisms before and after the main landslide. The assessment of ground displacements along the surface of the rupture in the 2019–2021 snowless periods was carried out using MT-InSAR methods. These displacements were 40 mm/year along the line of sight. The SBAS-InSAR results have allowed us to reveal displacements of great area in 2020 and 2021 snowless periods that were 30–40 mm/year along the line-of-sight. In general, the results obtained by MT-InSAR methods showed, on the one hand, the continuation of displacements along the surface of the rupture and on the other hand, some stabilization of the rate of landslide processes.
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Nunnari, G., G. Puglisi, and F. Guglielmino. "Inversion of SAR data in active volcanic areas by optimization techniques." Nonlinear Processes in Geophysics 12, no. 6 (September 30, 2005): 863–70. http://dx.doi.org/10.5194/npg-12-863-2005.

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Abstract. The inversion problem concerns the identification of parameters of a volcanic source causing observable changes in ground deformation data recorded in volcanic areas. In particular, this paper deals with the inversion of ground deformation measured by using SAR (Synthetic Aperture Radar) interferometry and an inversion approach formulated in terms of an optimization problem is proposed. Based on this inversion scheme, it is shown that the problem of inverting ground deformation data in terms of a single source, of Mogi or Okada type, is numerically well conditioned. In the paper, two case studies of inverting actual SAR data recorded on Mt. Etna during eruptions occurring in 1998 and 2001 are investigated, showing the suitability of the proposed technique.
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Ma, Deying, Mahdi Motagh, Guoxiang Liu, Rui Zhang, Xiaowen Wang, Bo Zhang, Wei Xiang, and Bing Yu. "Thaw Settlement Monitoring and Active Layer Thickness Retrieval Using Time Series COSMO-SkyMed Imagery in Iqaluit Airport." Remote Sensing 14, no. 9 (April 30, 2022): 2156. http://dx.doi.org/10.3390/rs14092156.

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Thaw consolidation of degrading permafrost is a serious hazard to the safety and operation of infrastructure. Monitoring thermal changes in the active layer (AL), the proportion of the soil above permafrost that thaws and freezes periodically, is critical to understanding the conditions of the top layer above the permafrost and regulating the construction, operation, and maintenance of facilities. However, this is a very challenging task using ground-based methods such as ground-penetrating radar (GPR) or temperature sensors. This study explores the integration of interferometric measurements from high-resolution X-band Synthetic Aperture Radar (SAR) images and volumetric water content (VWC) data from SoilGrids to quantify detailed spatial variations in active layer thickness (ALT) in Iqaluit, the territorial capital of Nunavut in Canada. A total of 21 SAR images from COSMO Sky-Med (CSK) were first analyzed using the freely connected network interferometric synthetic aperture radar (FCNInSAR) method to map spatial and temporal variations in ground surface subsidence in the study area. Subsequently, we built an ALT retrieval model by introducing the thaw settlement coefficient, which takes soil properties and saturation state into account. The subsidence measurements from InSAR were then integrated with VWC extracted from the SoilGrids database to estimate changes in ALT. For validation, we conducted a comparison between estimated ALTs and in situ measurements in the airport sector. The InSAR survey identifies several sites of ground deformation at Iqaluit, subsiding at rates exceeding 80 mm/year. The subsidence rate changes along the runway coincide with frost cracks and ice-wedge furrows. The obtained ALTs, ranging from 0 to 5 m, vary significantly in different sediments. Maximum ALTs are found for rock areas, while shallow ALTs are distributed in the till blanket (Tb), the intertidal (Mi) sediments, and the alluvial flood plain (Afp) sediment units. The intersection of taxiway and runway has an AL thicker than other parts in the glaciomarine deltaic (GMd) sediments. Our study suggests that combining high-resolution SAR imagery with VWC data can provide more comprehensive ALT knowledge for hazard prevention and infrastructure operation in the permafrost zone.
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Wei, Xu, and Feng Wenkai. "Application of Slope Radar (S-SAR) in Emergency Monitoring of the “11.03” Baige Landslide." Mathematical Problems in Engineering 2021 (October 27, 2021): 1–12. http://dx.doi.org/10.1155/2021/2060311.

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On October 11 and November 3, 2018, the disaster chain of landslide-barrier lake occurred twice in Baige Village, Xizang Province. After the second sliding of the landslide, the danger of the landslide dam was eliminated by the manual excavation of the drain grooves. During this period, a ground-based interferometric synthetic aperture radar (GB-InSAR) called “S-SAR” was utilized for real-time monitoring and analyzing 48 selected target pixels on the residual deformation bodies of landslides (divided into K1, K2, and K3 deformation zones) for 8 days. Through the real-time deformation map of pixels in the monitoring area obtained by S-SAR, the ranges of five strong deformation regions were identified and delineated. Based on the apparent cumulative deformation-time curve of each target pixel, the overall deformation law of K1, K2, and K3 deformation zones could be monitored and analyzed in real time. Based on a curve graph of the deformation rate, acceleration, and time of each target pixel, the K1, K2, and K3 deformation zones were within a uniform deformation stage. Taking the target pixel point and the corresponding time in which the deformation rate and deformation acceleration had a large, abrupt jump at the same time as the position and time of the near-slip failure, the 11 positions and moments of the near-slip failure were counted. The results presented here may represent a workable reference for emergency monitoring and early warning of similar sudden geological disasters.
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Monti-Guarnieri, Andrea, Marco Manzoni, Davide Giudici, Andrea Recchia, and Stefano Tebaldini. "Vegetated Target Decorrelation in SAR and Interferometry: Models, Simulation, and Performance Evaluation." Remote Sensing 12, no. 16 (August 7, 2020): 2545. http://dx.doi.org/10.3390/rs12162545.

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The paper addresses the temporal stability of distributed targets, particularly referring to vegetation, to evaluate the degradation affecting synthetic aperture radar (SAR) imaging and repeat-pass interferometry, and provide efficient SAR simulation schemes for generating big dataset from wide areas. The models that are mostly adopted in literature are critically reviewed, and aim to study decorrelation in a range of time (from hours to days), of interest for long-term SAR, such as ground-based or geosynchronous, or repeat-pass SAR interferometry. It is shown that none of them explicitly account for a decorrelation occurring in the short-term. An explanation is provided, and a novel temporal decorrelation model is proposed to account for that fast decorrelation. A formal method is developed to evaluate the performance of SAR focusing, and interferometry on a homogenous, stationary scene, in terms of Signal-to-Clutter Ratio (SCR), and interferometric coherence. Finally, an efficient implementation of an SAR simulator capable of handling the realistic case of heterogeneous decorrelation over a wide area is discussed. Examples are given by assuming two geostationary SAR missions in C and X band.
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Wang, Zheng, Zhenhong Li, Yanxiong Liu, Junhuan Peng, Sichun Long, and Jon Mills. "A New Processing Chain for Real-Time Ground-Based SAR (RT-GBSAR) Deformation Monitoring." Remote Sensing 11, no. 20 (October 20, 2019): 2437. http://dx.doi.org/10.3390/rs11202437.

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Due to the high temporal resolution (e.g., 10 s) required, and large data volumes (e.g., 360 images per hour) that result, there remain significant issues in processing continuous ground-based synthetic aperture radar (GBSAR) data. This includes the delay in creating displacement maps, the cost of computational memory, and the loss of temporal evolution in the simultaneous processing of all data together. In this paper, a new processing chain for real-time GBSAR (RT-GBSAR) is proposed on the basis of the interferometric SAR small baseline subset concept, whereby GBSAR images are processed unit by unit. The outstanding issues have been resolved by the proposed RT-GBSAR chain with three notable features: (i) low requirement of computational memory; (ii) insights into the temporal evolution of surface movements through temporarily-coherent pixels; and (iii) real-time capability of processing a theoretically infinite number of images. The feasibility of the proposed RT-GBSAR chain is demonstrated through its application to both a fast-changing sand dune and a coastal cliff with submillimeter precision.
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Liu, Linan, Wendy Zhou, and Marte Gutierrez. "Mapping Tunneling-Induced Uneven Ground Subsidence Using Sentinel-1 SAR Interferometry: A Twin-Tunnel Case Study of Downtown Los Angeles, USA." Remote Sensing 15, no. 1 (December 30, 2022): 202. http://dx.doi.org/10.3390/rs15010202.

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Synthetic Aperture Radar (SAR) interferometry is a formidable technique to monitor surface deformation with a millimeter detection resolution. This study applies the Persistent Scatter-Interferometric Synthetic Aperture Radar (PSInSARTM) technique to measure ground subsidence related to a twin-tunnel excavation in downtown Los Angeles, USA. The PSInSARTM technique is suitable for urban settings because urban areas have strong reflectors. The twin tunnels in downtown Los Angeles were excavated beneath a densely urbanized area with variable overburden depths. In practice, tunneling-induced ground settlement is dominantly vertical. The vertical deformation rate in this study is derived by combining Line of Sight (LOS) deformation velocities obtained from SAR images from both ascending and descending satellite orbits. Local and uneven settlements up to approximately 12 mm/year along the tunnel alignment are observed within the allowable threshold. No severe damages to aboveground structures were reported. Furthermore, ground movements mapped one year before tunnel construction indicate that no concentrated ground settlements pre-existed. A Machine Learning (ML)-based permutation feature importance method is used for a parametric study to identify dominant factors associated with the twin-tunneling induced uneven ground subsidence. Six parameters are selected to conduct the parametric study, including overburden thickness, i.e., the thickness of artificial fill and alluvium soils above the tunnel springline, the distance between the two tunnel centerlines, the depth to the tunnel springline, building height, the distance to the tunnel, and groundwater level. Results of the parametric analysis indicate that overburden thickness, i.e., the thickness of artificial fill and alluvium soils above the tunnel springline, is the dominant contributing factor, followed by the distance between tunnel centerlines, depth to the tunnel springline, and building height. Two parameters, the distance to the tunnel, and the groundwater level, play lesser essential roles than others. In addition, the geological profile provides comprehension of unevenly distributed ground settlements, which are geologically sensitive and more concentrated in areas with thick artificial fill and alluvium soils, low tunnel depth, and high groundwater levels.
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42

Marzano, F. S., S. Mori, M. Chini, L. Pulvirenti, N. Pierdicca, M. Montopoli, and J. A. Weinman. "Potential of high-resolution detection and retrieval of precipitation fields from X-band spaceborne synthetic aperture radar over land." Hydrology and Earth System Sciences 15, no. 3 (March 11, 2011): 859–75. http://dx.doi.org/10.5194/hess-15-859-2011.

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Abstract. X-band Synthetic Aperture Radars (X-SARs), able to image the Earth's surface at metric resolution, may provide a unique opportunity to measure rainfall over land with spatial resolution of about few hundred meters, due to the atmospheric moving-target degradation effects. This capability has become very appealing due to the recent launch of several X-SAR satellites, even though several remote sensing issues are still open. This work is devoted to: (i) explore the potential of X-band high-resolution detection and retrieval of rainfall fields from space using X-SAR signal backscattering amplitude and interferometric phase; (ii) evaluate the effects of spatial resolution degradation by precipitation and inhomogeneous beam filling when comparing to other satellite-based sensors. Our X-SAR analysis of precipitation effects has been carried out using both a TerraSAR-X (TSX) case study of Hurricane "Gustav" in 2008 over Mississippi (USA) and a COSMO-SkyMed (CSK) X-SAR case study of orographic rainfall over Central Italy in 2009. For the TSX case study the near-surface rain rate has been retrieved from the normalized radar cross section by means of a modified regression empirical algorithm (MREA). A relatively simple method to account for the geometric effect of X-SAR observation on estimated rainfall rate and first-order volumetric effects has been developed and applied. The TSX-retrieved rain fields have been compared to those estimated from the Next Generation Weather Radar (NEXRAD) in Mobile (AL, USA). The rainfall detection capability of X-SAR has been tested on the CSK case study using the repeat-pass coherence response and qualitatively comparing its signature with ground-based Mt. Midia C-band radar in central Italy. A numerical simulator to represent the effect of the spatial resolution and the antenna pattern of TRMM satellite Precipitation Radar (PR) and Microwave Imager (TMI), using high-resolution TSX-retrieved rain images, has been also set up in order to evaluate the rainfall beam filling phenomenon. As expected, the spatial average can modify the statistics of the high-resolution precipitation fields, strongly reducing its dynamics in a way non-linearly dependent on the rain rate local average value.
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43

Marzano, F. S., S. Mori, M. Chini, L. Pulvirenti, N. Pierdicca, M. Montopoli, and J. A. Weinman. "Potential of high-resolution detection and retrieval of precipitation fields from X-band spaceborne Synthetic Aperture Radar over land." Hydrology and Earth System Sciences Discussions 7, no. 5 (September 29, 2010): 7451–84. http://dx.doi.org/10.5194/hessd-7-7451-2010.

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Abstract. X-band Synthetic Aperture Radars (X-SARs), able to image the Earth's surface at metric resolution, may provide a unique opportunity to measure rainfall over land with spatial resolution of about few hundred meters, due to the atmospheric moving-target degradation effects. This capability has become very appealing due to the recent launch of several X-SAR satellites, even though several remote sensing issues are still open. This work is devoted to: (i) explore the potential of X-band high-resolution detection and retrieval of rainfall fields from space using X-SAR signal backscattering amplitude and interferometric phase; (ii) evaluate the effects of spatial resolution degradation by precipitation and inhomogeneous beam filling when comparing to other satellite-based sensors. Our X-SAR analysis of precipitation effects has been carried out using both a TerraSAR-X (TSX) case study of Hurricane "Gustav" in 2008 over Mississippi (USA) and a COSMO-SkyMed (CSK) X-SAR case study of orographic rainfall over Central Italy in 2009. For the TSX case study the near-surface rain rate has been retrieved from the normalized radar cross section by means of a modified regression empirical algorithm (MREA). A relatively simple method to account for the geometric effect of X-SAR observation on estimated rainfall rate and first-order volumetric effects has been developed and applied. The TSX-retrieved rain fields have been compared to those estimated from the Next Generation Weather Radar (NEXRAD) in Mobile (AL, USA). The rainfall detection capability of X-SAR has been tested on the CSK case study using the repeat-pass coherence response and qualitatively comparing its signature with ground-based Mt. Midia C-band radar in central Italy. A numerical simulator to represent the effect of the spatial resolution and the antenna pattern of TRMM satellite Precipitation Radar (PR) and Microwave Imager (TMI), using high-resolution TSX-retrieved rain images, has been also set up in order to evaluate the rainfall beam filling phenomenon. As expected, the spatial average can modify the statistics of the high-resolution precipitation fields, strongly reducing its dynamics in a way non-linearly dependent on the rainrate local average value.
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44

Wang, Yongzhe, Kun Chen, Ying Shi, Xu Zhang, Shi Chen, Ping’en Li, and Donghua Lu. "Source Model and Simulated Strong Ground Motion of the 2021 Yangbi, China Shallow Earthquake Constrained by InSAR Observations." Remote Sensing 13, no. 20 (October 15, 2021): 4138. http://dx.doi.org/10.3390/rs13204138.

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On 21 May 2021, an Mw 6.1 earthquake, causing considerable seismic damage, occurred in Yangbi County, Yunnan Province of China. To better understand the surface deformation pattern, source characteristics, seismic effect on nearby faults, and strong ground motion, we processed the ascending and descending SAR images using the interferometric synthetic aperture radar (InSAR) technique to capture the radar line-of-sight (LOS) directional and 2.5-dimensional deformation. The source model was inverted from the LOS deformation observations. We further analyzed the Coulomb failure stress (CFS) transfer and peak ground acceleration (PGA) simulation based on the preferred source model. The results suggest that the 2021 Yangbi earthquake was dextral faulting with the maximum slip of 0.9 m on an unknown blind shallow fault, and the total geodetic moment was 1.4 × 1018 Nm (Mw 6.06). Comprehensive analysis of the CFS transfer and geological tectonics suggests that the Dian–Xibei pull-apart basin is still suffering high seismic hazards. The PGA result demonstrates that the seismic intensity of this event reached up to VIII. The entire process from InSAR deformation to source modeling and strong ground motion simulation suggests that the InSAR technique will play an important role in the assessment of earthquake disasters in the case of the shortening of the SAR imaging interval.
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45

Gischig, V., S. Loew, A. Kos, J. R. Moore, H. Raetzo, and F. Lemy. "Identification of active release planes using ground-based differential InSAR at the Randa rock slope instability, Switzerland." Natural Hazards and Earth System Sciences 9, no. 6 (December 4, 2009): 2027–38. http://dx.doi.org/10.5194/nhess-9-2027-2009.

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Abstract. Five ground-based differential interferometric synthetic aperture radar (GB-DInSAR) surveys were conducted between 2005 and 2007 at the rock slope instability at Randa, Switzerland. Resultant displacement maps revealed, for the first time, the presence of an active basal rupture zone and a lateral release surface daylighting on the exposed 1991 failure scarp. Structures correlated with the boundaries of interferometric displacement domains were confirmed using a helicopter-based LiDAR DTM and oblique aerial photography. Former investigations at the site failed to conclusively detect these active release surfaces essential for kinematic and hazard analysis of the instability, although their existence had been hypothesized. The determination of the basal and lateral release planes also allowed a more accurate estimate of the currently unstable volume of 5.7±1.5 million m3. The displacement patterns reveal that two different kinematic behaviors dominate the instability, i.e. toppling above 2200 m and translational failure below. In the toppling part of the instability the areas with the highest GB-DInSAR displacements correspond to areas of enhanced micro-seismic activity. The observation of only few strongly active discontinuities daylighting on the 1991 failure surface points to a rather uniform movement in the lower portion of the instability, while most of the slip occurs along the basal rupture plane. Comparison of GB-DInSAR displacements with mapped discontinuities revealed correlations between displacement patterns and active structures, although spatial offsets occur as a result of the effective resolution of GB-DInSAR. Similarly, comparisons with measurements from total station surveys generally showed good agreement. Discrepancies arose in several cases due to local movement of blocks, the size of which could not be resolved using GB-DInSAR.
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46

Su, Yuhan, Honglei Yang, Junhuan Peng, Youfeng Liu, Binbin Zhao, and Mengyao Shi. "A Novel Near-Real-Time GB-InSAR Slope Deformation Monitoring Method." Remote Sensing 14, no. 21 (November 5, 2022): 5585. http://dx.doi.org/10.3390/rs14215585.

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In the past two decades, ground-based synthetic aperture radars (GB-SARs) have developed rapidly, providing a large amount of SAR data in minutes or even seconds. However, the real-time processing of big data is a challenge for the existing GB-SAR interferometry (GB-InSAR) technology. In this paper, we propose a near-real-time GB-InSAR method for monitoring slope surface deformation. The proposed method uses short baseline SAR data to generate interferograms to improve temporal coherence and reduce atmospheric interference. Then, based on the wrapped phase of each interferogram, a network method is used to estimate and remove systematic errors (such as atmospheric delay, radar center shift error, etc.). After the phase unwrapping, a least squares estimator is used for the overall solution to obtain the initial deformation parameters. When new data are added, a sequential estimator is used to combine the previous processing results and dynamically update the deformation parameters. Sequential estimators could avoid repeated calculations and improve data processing efficiency. Finally, the method is validated with the measured data. The results show that the average deviation between the proposed method and the overall estimation was less than 0.01 mm, which could be considered a consistent estimation accuracy. In addition, the calculation time of the sequential estimator was less sensitive than the total amount of data, and the time-consuming growth rate of each additional period of data was about 1/10 of the overall calculation. In summary, the new method could quickly and effectively obtain high-precision surface deformation information and meet the needs of near-real-time slope deformation monitoring.
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47

Wnuk, Kendall, Wendy Zhou, and Marte Gutierrez. "Mapping Urban Excavation Induced Deformation in 3D via Multiplatform InSAR Time-Series." Remote Sensing 13, no. 23 (November 23, 2021): 4748. http://dx.doi.org/10.3390/rs13234748.

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Excavation of a subway station and rail crossover cavern in downtown Los Angeles, California, USA, induced over 1.8 cm of surface settlement between June 2018 and February 2019 as measured by a ground-based monitoring system. Point measurements of surface deformation above the excavation were extracted by applying Interferometric Synthetic Aperture Radar (InSAR) time-series analyses to data from multiple sensors with different wavelengths. These sensors include C-band Sentinel-1, X-band COSMO-SkyMed, and L-band Uninhabited Aerial Vehicle SAR (UAVSAR). The InSAR time-series point measurements were interpolated to continuous distribution surfaces, weighted by distance, and entered into the Minimum-Acceleration (MinA) algorithm to calculate 3D displacement values. This dataset, composed of satellite and airborne SAR data from X, C, and L band sensors, revealed previously unidentified deformation surrounding the 2nd Street and Broadway Subway Station and the adjacent rail crossover cavern, with maximum vertical and horizontal deformations reaching 2.5 cm and 1.7 cm, respectively. In addition, the analysis shows that airborne SAR data with alternative viewing geometries to traditional polar-orbiting SAR satellites can be used to constrain horizontal displacements in the North-South direction while maintaining agreement with ground-based data.
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48

Raspini, F., C. Loupasakis, D. Rozos, and S. Moretti. "Advanced interpretation of land subsidence by validating multi-interferometric SAR data: the case study of the Anthemountas basin (Northern Greece)." Natural Hazards and Earth System Sciences 13, no. 10 (October 9, 2013): 2425–40. http://dx.doi.org/10.5194/nhess-13-2425-2013.

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Abstract. The potential of repeat-pass space borne SAR (Synthetic Aperture Radar) interferometry has been exploited to investigate spatial patterns of land subsidence in the Anthemountas basin, in the northern part of Greece. The PSI (Persistent Scatterer Interferometry) approach, based on the processing of long series of SAR acquisitions, has been applied to forty-two images acquired in 1995–2001 by ERS1/2 satellites. Interferometric results have been analysed at a basin scale as support for land motion mapping and at a local scale for the characterisation of ground motion events affecting the village of Perea in the Thermaikos municipality and the "Macedonia" international airport. PSI results revealed a moderate subsidence phenomenon along the wider coastal zone of Anthemountas basin corresponding to intense groundwater extraction. Highest values, exceeding −20 mm yr−1, were measured in the airport area where the thickest sequence of compressible Quaternary sediments occurs. Intense subsidence has been detected also in the Perea village (maximum deformation of −10 to −15 mm yr−1), where a series of fractures, causing damages to both buildings and infrastructure, occurred in 2005–2006.
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49

Ozawa, Taku, Yosuke Aoki, Satoshi Okuyama, Xiaowen Wang, Yousuke Miyagi, and Akira Nohmi. "Database of Crustal Deformation Observed by SAR: Improving Atmospheric Delay Mitigation for Satellite SAR Interferometry and Developing L-Band Multi-Type Portable SAR." Journal of Disaster Research 14, no. 5 (August 1, 2019): 713–27. http://dx.doi.org/10.20965/jdr.2019.p0713.

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Spaceborne synthetic aperture radar (SAR) and ground-based radar interferometers (GBRIs) can be used to detect spatially detailed crustal deformations that are difficult to detect by on-site observations, the Global Navigation Satellite System, tiltmeters, and so on. To make such crustal deformation information readily available to those engaged in evaluating volcanic activities and researching the mechanisms, we are preparing a database within the Japan Volcanological Data Network data sharing system to store crustal deformation detected by spaceborne SAR and GBRIs (Subtheme 2-1, Project B, the Integrated Program for Next Generation Volcano Research and Human Resource Development). In this study, we examined methods to reduce atmospheric delay noise in SAR interferometry using the numerical weather model and determined the methods for resampling the analytical values of the numerical weather model and estimating atmospheric delay to efficiently determine atmospheric delay. We show that the atmospheric delay can be estimated with higher accuracy by properly combining the isobaric surface and ground surface data of the mesoscale model (MSM) provided by the Japan Meteorological Agency. We are developing a multi-type portable SAR system as a GBRI system such that it would allow campaign observations whenever increased volcanic activities are observed and acquire crustal deformation with a higher temporal resolution than spaceborne SAR for storage in the database. This system employs L-band radar, which has a higher penetrability against vegetation. Two modes of observations are possible: ground-based SAR and car-borne SAR. The prototype was fabricated to conduct experiments necessary to develop a working model. The experimental observations was carried out around Asama volcano, and we confirmed that clear fringe was obtained.
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50

Matano, Fabio. "Analysis and Classification of Natural and Human-Induced Ground Deformations at Regional Scale (Campania, Italy) Detected by Satellite Synthetic-Aperture Radar Interferometry Archive Datasets." Remote Sensing 11, no. 23 (November 28, 2019): 2822. http://dx.doi.org/10.3390/rs11232822.

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The high levels of geo-hydrological, seismic, and volcanic hazards in the Campania region prompted full data collection from C-band satellites ERS-1/2, ENVISAT, and RADARSAT within regional (TELLUS) and national (PST-A) projects. The quantitative analysis, interpretation, and classification of natural and human-induced slow-rate ground deformations across a span of two decades (1992–2010) was performed at regional scale (Campania, Italy) by using interferometric archive datasets, based on the Persistent Scatterer Interferometry approach. As radar satellite sensors have a side-looking view, the post-processing of the interferometric datasets allows for the evaluation of two spatial components (vertical and E-W horizontal ones) of ground deformation, while the N-S horizontal component cannot be detected. The ground deformation components have been analyzed across 89.5% of the Campania territory within a variety of environmental, topographical, and geological conditions. The main part (57%) of the regional territory was characterized during 1992–2010 by stable areas, where SAR signals do not have recorded significant horizontal and vertical components of ground deformation with an average annual rate greater than +1 mm/yr or lower than −1 mm/yr. Within the deforming areas, the coastal plains are characterized by widespread and continuous strong subsidence signals due to sediment compaction locally enhanced by human activity, while the inner plain sectors show mainly scattered spots with locally high subsidence in correspondence of urban areas, sinkholes, and groundwater withdrawals. The volcanic sectors show interplaying horizontal and vertical trends due to volcano-tectonic processes, while in the hilly and mountain inner sectors the ground deformation is mainly controlled by large-scale tectonic activity and by local landslide activity. The groundwater-related deformation is the dominant cause of human-caused ground deformation. The results confirm the importance of using Persistent Scatterer Interferometry data for a comprehensive understanding of rates and patterns of recent ground deformation at regional scale also within tectonically active areas as in Campania region.
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